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Academic literature on the topic 'Entity Grid Model'
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Journal articles on the topic "Entity Grid Model"
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Deng, Xingye, Canwei Liu, Hualiang Liu, Lei Chen, Yuyan Guo, and Heding Zhen. "Enhanced Density Peak-Based Power Grid Reactive Voltage Partitioning." Energies 16, no. 17 (2023): 6125. http://dx.doi.org/10.3390/en16176125.
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Clustering-based reactive voltage partitioning is successful in reducing grid cascading faults, by using clustering methods to categorize different power-consuming entities in the power grid into distinct regions. In reality, each power-consuming entity has different electrical characteristics. Additionally, due to the irregular and uneven distribution of the population, the distribution of electricity consumption is also irregular and uneven. However, the existing method neglects the electrical difference among each entity and the irregular and uneven density distribution of electricity consumption, resulting in poor accuracy and adaptability of these methods. To address these problems, an enhanced density peak model-based power grid reactive voltage partitioning method is proposed in this paper, called EDPVP. First, the power grid is modeled as a weighted reactive network to consider entity electrical differences. Second, the novel local density and density following distance are designed to enhance the density peak model to address the problem that the traditional density peak model cannot adapt to weighted networks. Finally, the enhanced density peak model is further equipped with an optimized cluster centers selection strategy and an updated remaining node assignment strategy, to better identify irregular and uneven density distribution of electricity consumption, and to achieve fast and accurate reactive voltage partition. Experiments on two real power grids demonstrate the effectiveness of the EDPVP.
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Yokono, Hikaru, and Manabu Okumura. "Local Coherence Model Based on Entity Grid Augmented with Text Cohesion." Journal of Natural Language Processing 17, no. 1 (2010): 161–82. http://dx.doi.org/10.5715/jnlp.17.1_161.
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Bao, Guang Bin, Ke Xia Zhang, and Hong Zhao. "Research on Information Technology with Modeling and Simulating of Video Grid." Advanced Materials Research 886 (January 2014): 655–59. http://dx.doi.org/10.4028/www.scientific.net/amr.886.655.
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Based on video grid structure, A Video Grid model was established using AnyLogic simulation software. First, the components required for modeling functions are introduced, and then create a model entity, video service processes, animation and analysis chart. Simulation results show that the AnyLogic-based video grid model, the model parameters can be adjusted, not only from the macroscopic dynamic observation of the entire system dynamics, but also from the microscopic measurement of the specified components. The construction of the actual video grid can provide a decision support.
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Yin, Didi, Siyuan Cheng, Boxu Pan, Yuanyuan Qiao, Wei Zhao, and Dongyu Wang. "Chinese Named Entity Recognition Based on Knowledge Based Question Answering System." Applied Sciences 12, no. 11 (2022): 5373. http://dx.doi.org/10.3390/app12115373.
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The KBQA (Knowledge-Based Question Answering) system is an essential part of the smart customer service system. KBQA is a type of QA (Question Answering) system based on KB (Knowledge Base). It aims to automatically answer natural language questions by retrieving structured data stored in the knowledge base. Generally, when a KBQA system receives the user’s query, it first needs to recognize topic entities of the query, such as name, location, organization, etc. This process is the NER (Named Entity Recognition). In this paper, we use the Bidirectional Long Short-Term Memory-Conditional Random Field (Bi-LSTM-CRF) model and introduce the SoftLexicon method for a Chinese NER task. At the same time, according to the analysis of the characteristics of application scenario, we propose a fuzzy matching module based on the combination of multiple methods. This module can efficiently modify the error recognition results, which can further improve the performance of entity recognition. We combine the NER model and the fuzzy matching module into an NER system. To explore the availability of the system in some specific fields, such as a power grid field, we utilize the power grid-related original data collected by the Hebei Electric Power Company to improve our system according to the characteristics of data in the power grid field. We innovatively make the dataset and high-frequency word lexicon in the power grid field, which makes our proposed NER system perform better in recognizing entities in the field of power grid. We used the cross-validation method for validation. The experimental results show that the F1-score of the improved NER model on the power grid dataset reaches 92.43%. After processing the recognition results by using the fuzzy matching module, about 99% of the entities in the test set can be correctly recognized. It proves that the proposed NER system can achieve excellent performance in the application scenario of a power grid. The results of this work will also fill the gap in the research of intelligent customer-service-related technologies in the power grid field in China.
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Irawan, Dandan. "Positioning Koperasi Melalui Pendekatan ICA Grid Model." Coopetition : Jurnal Ilmiah Manajemen 12, no. 3 (2021): 465–76. http://dx.doi.org/10.32670/coopetition.v12i3.753.
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In order to know whether a cooperative organization is really a cooperative in a true sense, it is necessary to first look at its identity. The identity of a cooperative is a basic characteristic inherent in a cooperative since its birth. It undergoes a very long and crystalline process of growth and maturity, thus placing the cooperative as a business entity that has a positioning for its members. Cooperatives operate in a space that is limited by their identity and by the rules that apply to free market players such as corporations. Cooperatives also play in a competitive market economy and also in an environment where market conditions sometimes do not apply. Therefore for cooperatives it is important to know where their position is at certain times in an effort to maintain and secure their identity, with the aim of maintaining their existence as a cooperative.
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Luo, Jingtang, Shiying Yao, Changming Zhao, Jie Xu, and Jim Feng. "A Federated Named Entity Recognition Model with Explicit Relation for Power Grid." Computers, Materials & Continua 75, no. 2 (2023): 4207–16. http://dx.doi.org/10.32604/cmc.2023.034439.
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Sharma, Dolly, Shailendra Singh, and Mamta Mittal. "Trust Models in Grid Computing: A Review." Recent Patents on Engineering 13, no. 2 (2019): 94–100. http://dx.doi.org/10.2174/1872212112666180427143757.
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Background: Grid computing relates to a pool of resources to be shared by users in Grid Environment. Security of the resources from users and vice-versa is a significant issue. This is where the notion of trust comes into existence. A number of researchers have proposed models for evaluation of trust in grid computing, but they fail to spot one or the other parameters for trust evaluation. The essence of trust models in grid computing is that they offer autonomic trust management. An autonomic trust model has been patented by Z. Yan and C. Prehofer in 2009. Another patent was published by Anna University in 2010 to evaluate the trustworthiness of a resource provider in Grid environment. Objective: This paper firstly focuses and illustrates these essential parameters. Based on these parameters, further, a comparison of some existing models for trust evaluation is shown. Finally, common parameters missed out by various models have been highlighted giving way for improvements of Trust model. Methods: A Trust evaluation model has been proposed by us previously based on a number of real-world trust evaluation parameters. This model sees trust as a three-dimensional entity. Trust is based on Dempter Shafer’s theory in which trust is calculated mathematically. Results: Software trust needs to be calculated mathematically. There are a large number of real-world parameters that need to be included for evaluating trust. Conclusion: As trust models in research are based on simulation techniques, so it is important to include real-world factors that affect trust value of one entity on other. Some of those parameters, missed by most of the models have been identified for inclusion in future trust models.
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Mirz, Markus, Lukas Razik, Jan Dinkelbach, et al. "A Cosimulation Architecture for Power System, Communication, and Market in the Smart Grid." Complexity 2018 (2018): 1–12. http://dx.doi.org/10.1155/2018/7154031.
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Smart grids evolve rapidly towards a system that includes components from different domains, which makes interdisciplinary modelling and analysis indispensable. In this paper, we present a cosimulation architecture for smart grids together with a comprehensive data model for the holistic representation of the power system, the communication network, and the energy market. Cosimulation is preferred over a monolithic approach since it allows leveraging the capabilities of existing, well-established domain-specific software. The challenges that arise in a multidomain smart grid cosimulation are identified for typical use cases through a discussion of the recent literature. Based on the identified requirements and use cases, a joint representation of the smart grid ecosystem is facilitated by a comprehensive data model. The proposed data model is then integrated in a software architecture, where the domain-specific simulators for the power grid, the communication network, and the market mechanisms are combined in a cosimulation framework. The details of the software architecture and its implementation are presented. Finally, the implemented framework is used for the cosimulation of a virtual power plant, where battery storages are controlled by a novel peak-shaving algorithm, and the battery storages and the market entity are interfaced through a communication network.
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Song, Niu, and Li. "Individual Behavior Simulation Based on Grid Object and Agent Model." ISPRS International Journal of Geo-Information 8, no. 9 (2019): 388. http://dx.doi.org/10.3390/ijgi8090388.
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For the simplicity of spatial modeling in Cellular Automaton (CA) and the complexity of vector spatial expression in the Multi-Agent System (MAS), the concept of grid object as the spatial model of individual behavior simulation was proposed with spatial information, semantic information, and connection relationship of geographic entity. Then, by incorporating the MAS, the method for individual behavior simulation with the Grid Object and Agent Model (GOAM) was demonstrated. Meanwhile, a prototype system including the three subsystems was developed based on the GOAM, and experiments were conducted for two cases in different spatial environments. The prototype system can be used to obtain grid object data with 3D model data, to compute and simulate the behavior of individuals, and to render individuals. The two cases involve goal-driven behavior in both indoor and outdoor environments as examples to evaluate the validity of the GOAM and to provide a reference for building individual behavior simulation with the GOAM in other scenarios.
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Liang, Kun, Baoxian Zhou, Yiying Zhang, Yiping Li, Bo Zhang, and Xiankun Zhang. "PF2RM: A Power Fault Retrieval and Recommendation Model Based on Knowledge Graph." Energies 15, no. 5 (2022): 1810. http://dx.doi.org/10.3390/en15051810.
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Energy saving and emission reduction have become common concerns in countries around the world. In China, with the implementation of the new strategy of “carbon peak and neutrality” and the rapid development of the new smart grid infrastructure, the amount of data of actual power grid dispatching and fault analysis show exponential growth, which has led to phenomena such as poor supervision effectiveness and difficulty in handling faults in the process of grid operation and maintenance. Existing research on retrieval recommendation methods has had a lower accuracy rate at cold-start due to a small sample of user interactions. In addition, the cumulative learning of user personalization during general retrieval results in a poor perception of potential interest. By constructing a power knowledge graph, this paper presents a power fault retrieval and recommendation model (PF2RM) based on user-polymorphic perception. This model includes two methods: the power fault retrieval method (PFR) and the user-polymorphic retrieval recommendation method (UPRR). First, we take the power grid fault dispatching business as the core and reconstruct the ontology layer of the power knowledge graph. The PFR method is used to design the graph-neighbor fault entity cluster to enhance the polymerization degree of a fault implementation scenario. This method can solve the search cold-start recommendation problem. At the same time, the UPRR method aims to form user retrieval subgraphs of the past-state and current-state and make a feature matching for the graph-neighbor fault entity cluster, and then realize the accurate prediction of the user’s general search intention. The model is compared with other current classical models through the evaluation of multiple recommendation evaluation metrics, and the experimental results show that the model has a 3–8% improvement in the cold-start recommendation effect and 2–10% improvement in regular retrieval. The model has the best average recommendation performance in multiple metrics and has good results in fault analysis and retrieval recommendation. It plays a helpful role in intelligent operation and maintenance of the power grid and auxiliary decision-making, and effectively improves the reliability of the power grid.